Compact cities are recognized as sustainable urban forms rather than sprawl developments. Such cities are characterized by high density, land use diversity, accessibility, and efficient public transportation. However, few studies investigate how and how much these parameters affect and relate to compact cities. For instance, although mixed land use is the main key planning principle of compact development, no standard method exists for quantifying, measuring, and evaluating this parameter. This study performs a compact development analysis of Kajang City (Malaysia) with emphasis on evaluating and discussing the importance of mixed land use development. First, the land use diversity of Kajang City was measured. Second, the probability map of mixed land use developments was predicted using a weights-of-evidence (WoE) model. Finally, the importance of mixed land use for compact cities was evaluated using multicriteria decision analysis (MCDA). The created mixed land use probability map was validated using the receiver operating characteristic (ROC) technique. In addition, the 75% similarity between mixed land use and compact development suitability maps highlighted the importance of mixed land use development for compact cities. Results can be used as preliminary guidelines for local governments and planners regarding compact development and management to achieve sustainable urban forms.

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In recent decades, compact urban development and smart cities are recognised as most sustainable urban form in an effort to protect natural environment. Therefore, evaluation of existing compactness and sustainability of an area is an essential task before the real development takes place. In the literature, it is possible to see some studies on city's compactness assessment and most of them have considered only a few aspects of compact development analysis. This paper aims to analyse urban sustainability of Kajang city (Malaysia) through a comprehensive city compactness assessment using geographical information system and radar remote sensing technology. To measure building density, a RADAR image of the study area was used to extract built-up areas with the aid of pixel-based and object-based classification schemes. Mixed land use development, urban density and intensity were the main indicators of the analysis. Finally, multicriteria decision-making and Bayes theorems were applied for overall compactness assessment. Building density analysis was validated using standard confusion matrix, which showed more than 90% accuracy. Similarly, the root-mean squared error showed 0.35 for object-based classification. The results classified the zones of the Kajang city in the range of least to most compact zones with the compactness value of 0.00273-0.0146, respectively. The results obtained in this study can help local government to improve the compactness of least compact zones to make Kajang city more sustainable. Furthermore, the results revealed that efficient public transportation and proper community facilities are the key factors to achieve sustainable urban development.

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This paper presents an evaluation of two bivariate statistical approaches, frequency ratio (FR) and weights-of-evidence (WoE) for landslide susceptibility mapping (LSM) at south-western part of Saudi Arabia, Jizan region. Landslide locations were identified and mapped from interpretation of high resolution satellite images (GeoEye 0.5 m and QuikeBird 0.6m), topographic maps (scale of 1:10,000), historical records, and extensive field surveys. A total of 106 landslide locations were mapped using Arc-GIS software and divided into two groups, 75% and 25% of landslide locations were used for training and validation of models, respectively. Eleven landslide conditioning factors such as elevation, slope, curvature, aspect, lithology, topographic wetness index (TWI), normalized difference vegetation index (NDVI), proximity to lineament, roads and rivers were considered in this evaluation. The effects of these factors on landslide occurrence were assessed using aforementioned bivariate statistical approaches. For validation, the models results were compared with landslide locations which were not used during the models building. Subsequently, the receiver operating characteristic (ROC) curves were established and area under the curves (AUC) was calculated for the landslide susceptibility maps using the success (training data) and prediction (validation data) rates. The results showed that the area under the curve for success rates are 0.861 (86.1%) and 0.839 (83.9%) and for prediction rates are 0.796 (79.6%) and 0.791 (79.1%), respectively for frequency ratio and weight-of-evidence models. The resulting landslide susceptibility maps showed five classes of susceptibility such as very high, high, moderate, low, and very low. The percentage of existing training and validating landslides data in high and very high zones of the susceptibility maps were calculated to be 90.02% and 76.03% for frequency ratio model and 88.33% and 79.3% for weight-of-evidence model, respectively. The results revealed that the frequency ratio and weights-of-evidence models produced reasonable accuracy. The resultant maps would be useful and can also help planners for general choosing favorable locations for development schemes, such as infrastructural, buildings, road constructions, and environmental protection.

Rapid and unorganized urban growth brings about urban sprawl, which leads to the increase in the number of abandoned lands and brownfields within the cities. Revitalization and redevelopment of these areas is one of the key factors of compact urban development to achieve urban sustainability. However, not much research work has been done on the redevelopment of brownfield on the base of compact urban development paradigm in the recent literature. Most researches on this field have mainly considered a single brownfield site for redevelopment on the bases of local neighborhood demand and characteristics. The current paper proposes a brownfields land use change modeling process according to a compact city paradigm in a larger scale perspectives rather than local aspects. The proposed model is a statistical-based weights-of-evidence (WoE) approach in the GIS environment. The growth of three main land use types in Kajang city, Malaysia was predicted using several compact development parameters and other urban and physical site characteristics. Maps that have been created with this process were validated by actual growth maps of these land use types using an area under curve (AUC) technique. The AUC of residential, commercial and industrial land use were gained as 77.4, 78, and 67 %, respectively. Finally, these maps were aggregated with an existing brownfields map in order to project future land use types according to planning strategies, as well as compact development characteristics. Results indicate that according to potential and suitability of the site and neighborhood properties, each brownfield can serve the community as single or mixture of several land use types. It is concluded that the combination of land use change modeling techniques and compact urban development theory in GIS environment can provide a strong tool for brownfields redevelopment planning and strategies.

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